Committed processing rates for shared resources

ABSTRACT

Customers of a shared-resource environment can provision resources in a fine-grained manner that meets specific performance requirements. A customer can provision a data volume with a committed rate of Input/Output Operations Per Second (IOPS) and pay only for that commitment (plus any overage), and the amount of storage requested. The customer will then at any time be able to complete at least the committed rate of IOPS. If the customer generates submissions at a rate that exceeds the committed rate, the resource can still process at the higher rate when the system is not under pressure. Even under pressure, the system will deliver at least the committed rate. Multiple customers can be provisioned on the same resource, and more than one customer can have a committed rate on that resource. Customers without committed or guaranteed rates can utilize the uncommitted portion, or committed portions that are not being used.

BACKGROUND

As an increasing number of applications and services are being madeavailable over networks such as the Internet, an increasing number ofcontent, application, and/or service providers are turning totechnologies such as remote resource sharing cloud computing. Cloudcomputing, in general, is an approach to providing access to electronicresources through services, such as Web services, where the hardwareand/or software used to support those services is dynamically scalableto meet the needs of the services at any given time. A user or customertypically will rent, lease, or otherwise pay for access to resourcesthrough the cloud, and thus does not have to purchase and maintain thehardware and/or software to provide access to these resources.

In some environments, multiple users can share resources such as datarepositories, wherein the users can concurrently send multiple readand/or write requests to be executed against the same data instance, forexample. Problems can arise, however, when the number of concurrentrequests exceeds the ability of the instance to process those requests.In one example, a data server for an instance might get into an overloadsituation and begin putting back pressure on the incoming requests inorder to reduce the rate of incoming requests and allow the system torecover from the overload situation. As a result of the push back,however, customers might not receive a desired or necessary rate ofrequest processing, which can upset the customers and in some casescause the customers to look to other providers for data storage andsimilar resources. Certain conventional approaches attempt to throttlerequests when a particular customer exceeds some usage threshold, forexample, but these approaches tend to be reactive and can still lead tothe other customers of a resource experiencing slow downs and overloadsituations.

BRIEF DESCRIPTION OF THE DRAWINGS

Various embodiments in accordance with the present disclosure will bedescribed with reference to the drawings, in which:

FIG. 1 illustrates an environment in which various embodiments can beimplemented;

FIG. 2 illustrates an example separation of management and hostcomponents that can be used in accordance with various embodiments;

FIG. 3 illustrates an example allocation for multiple customers that canbe used in accordance with various embodiments;

FIG. 4 illustrates an example allocation across multiple resourceinstances that can be used in accordance with various embodiments;

FIG. 5 illustrates an example process for obtaining a guaranteed levelof service through the control plane to be performed in the data planein accordance with one embodiment; and

FIG. 6 illustrates an example environment that can utilize resourceaccess approaches in accordance with various embodiments.

DETAILED DESCRIPTION

Systems and methods in accordance with various embodiments of thepresent disclosure may overcome one or more of the aforementioned andother deficiencies experienced in conventional approaches to managingaspects of resource sharing and allocation in an electronic environment.For example, various embodiments enable users to request a specificquality of service or level of processing, such as a minimum and/orcommitted rate of input/output operations per second (IOPS) against aparticular resource. The requested amount can be any appropriate amount,which can be less than the total amount provided by the respectiveresource, providing a finer granularity than is possible withconventional approaches. Multiple customers can be assigned to a singleresource, such as a data server, with each of the customers potentiallyreceiving a guaranteed level of service. In various embodiments,customers requesting rate commitments that cannot be provided by asingle available resource can have the commitment spread across multipleresources or resource instances. Each resource can have an acceptablelevel of guarantees (e.g., rate commitments), which can be a percentageor portion of the total amount available on the resource, the fullamount available, or in some cases greater than the total amount. Sincecustomers often will not use the entire committed amount (e.g., theguaranteed rate of IOPS), certain resources can have resourcecommitments above 100% of the available capacity. Further, othercustomers can be provisioned on those resources as well. If less thanthe full available capacity of a resource is committed to guaranteeservice levels, the remaining customers can share the un-committedcapacity. When one of the customers with a guarantee is using less thanthe guaranteed amount, the other customers can also utilize this unusedcapacity, until such time as the guaranteed customer requests to usethat capacity. Such an approach improves the quality of service fornon-committed customers, while decreasing the cost of providingguaranteed service levels.

Customers in certain embodiments can provision resources in afine-grained manner that matches the customer's specific performancerequirements. If, for example, a customer has a database that requires300 IOPS, the customer can provision a data volume with a committed rateof 300 IOPS and pay only for that commitment, plus the amount of storagerequested. The customer will be able to complete at least 300 IOPS,averaged over some period, for the data volume. If the customer submits500 IOPS on average, the volume may still complete 500 per second overtime if the system is not under pressure; however, the system willdeliver at least the committed 300 over time even when under pressure.

In a conventional system, a customer wanting a certain IOPS ratetypically has to obtain the appropriate number of physical disks and payfor the amount of storage on those disks. For typical workloads, thecustomer then has to overbuy considerably on storage to get the desiredIOPS rate. Using approaches of the various embodiments, customer canobtain a guaranteed quality of service for a shared storage solution, ata level of granularity not possible with conventional systems. The finergranularity can also represent significant cost savings for a customer,as opposed to buying or renting dedicated hardware.

Systems and methods in accordance with various embodiments are operableto management access to resources such as data storage. In at least someembodiments, these approaches include providing a block data storageservice that uses multiple server storage systems to reliably storeblock data that may be accessed and used over one or more networks byany of various users, applications, processes, and/or services. Users ofthe block data storage service may each create one or more block datastorage volumes that each have a specified amount of block data storagespace, and may initiate use of such a block data storage volume (alsoreferred to as a “volume” herein) by one or more executing programs,with at least some such volumes having copies stored by two or more ofthe multiple server storage systems so as to enhance volume reliabilityand availability to the executing programs. As one example, the multipleserver block data storage systems that store block data may in someembodiments be organized into one or more pools or other groups thateach have multiple physical server storage systems co-located at ageographical location, such as in each of one or more geographicallydistributed data centers, and the program(s) that use a volume stored ona server block data storage system in a data center may execute on oneor more other physical computing systems at that data center.

In addition, in at least some embodiments, applications that access anduse one or more such non-local block data storage volumes over one ormore networks may each have an associated node manager that manages theaccess to those non-local volumes by the program, such as a node managermodule that is provided by the block data storage service and/or thatoperates in conjunction with one or more Block Data Service (BDS) SystemManager modules. For example, a first user who is a customer of theblock data storage service may create a first block data storage volume,and execute one or more program copies on one or more computing nodesthat are instructed to access and use the first volume (e.g., in aserial manner, in a simultaneous or other overlapping manner, etc.).When an application executing on a computing node initiates use of anon-local volume, the application may mount or otherwise be providedwith a logical block data storage device that is local to the computingnode and that represents the non-local volume, such as to allow theexecuting program to interact with the local logical block data storagedevice in the same manner as any other local hard drive or otherphysical block data storage device that is attached to the computingnode (e.g., to perform read and write data access requests, to implementa file system or database or other higher-level data structure on thevolume, etc.). For example, in at least some embodiments, arepresentative logical local block data storage device may be madeavailable to an executing program via use of an appropriate technology,such as GNBD (“Global Network Block Device”) technology. In addition,when an application interacts with the representative local logicalblock data storage device, the associated node manager may manage thoseinteractions by communicating over one or more networks with at leastone of the server block data storage systems that stores a copy of theassociated non-local volume (e.g., in a manner transparent to theexecuting program and/or computing node) so as to perform theinteractions on that stored volume copy on behalf of the executingprogram. Furthermore, in at least some embodiments, at least some of thedescribed techniques for managing access of applications and services tonon-local block data storage volumes are automatically performed byembodiments of a Node Manager module.

In at least some embodiments, block data storage volumes (or portions ofthose volumes) may further be stored on one or more remote archivalstorage systems that are distinct from the server block data storagesystems used to store volume copies. In various embodiments, the one ormore remote archival storage systems may be provided by the block datastorage service (e.g., at a location remote from a data center or othergeographical location that has a pool of co-located server block datastorage systems), or instead may be provided by a remote long-termstorage service and used by the block data storage, and in at least someembodiments the archival storage system may store data in a format otherthan block data (e.g., may store one or more chunks or portions of avolume as distinct objects).

In some embodiments, at least some of the described techniques areperformed on behalf of a program execution service that managesexecution of multiple programs on behalf of multiple users of theprogram execution service. In some embodiments, the program executionservice may have groups of multiple co-located physical host computingsystems, and may execute users' programs on those physical hostcomputing systems, such as under control of a program execution service(“PES”) system manager, as discussed in greater detail below. In suchembodiments, users of the program execution service (e.g., customers ofthe program execution service who pay fees to use the program executionservice) who are also users of the block data storage service mayexecute programs that access and use non-local block data storagevolumes provided via the block data storage service. In otherembodiments, a single organization may provide at least some of bothprogram execution service capabilities and block data storage servicecapabilities (e.g., in an integrated manner, such as part of a singleservice), while in yet other embodiments the block data storage servicemay be provided in environments that do not include a program executionservice (e.g., internally to a business or other organization to supportoperations of the organization).

In addition, the host computing systems on which programs execute mayhave various forms in various embodiments. Multiple such host computingsystems may, for example, be co-located in a physical location (e.g., adata center), and may be managed by multiple node manager modules thatare each associated with a subset of one or more of the host computingsystems. At least some of the host computing systems may each includesufficient computing resources (e.g., volatile memory, CPU cycles orother CPU usage measure, network bandwidth, swap space, etc.) to executemultiple programs simultaneously, and, in at least some embodiments,some or all of the computing systems may each have one or morephysically attached local block data storage devices (e.g., hard disks,tape drives, etc.) that can be used to store local copies of programs tobe executed and/or data used by such programs. Furthermore, at leastsome of the host computing systems in some such embodiments may eachhost multiple virtual machine computing nodes that each may execute oneor more programs on behalf of a distinct user, with each such hostcomputing system having an executing hypervisor or other virtual machinemonitor that manages the virtual machines for that host computingsystem. For host computing systems that execute multiple virtualmachines, the associated node manager module for the host computingsystem may in some embodiments execute on at least one of multiplehosted virtual machines (e.g., as part of or in conjunction with thevirtual machine monitor for the host computing system), while in othersituations a node manager may execute on a physical computing systemdistinct from one or more other host computing systems being managed.

The server block data storage systems on which volumes are stored mayalso have various forms in various embodiments. In at least someembodiments, some or all of the server block data storage systems may bephysical computing systems similar to the host computing systems thatexecute programs, and in some such embodiments may each execute serverstorage system software to assist in the provision and maintenance ofvolumes on those server storage systems. For example, in at least someembodiments, one or more of such server block data storage computingsystems may execute at least part of the BDS System Manager, such as ifone or more BDS System Manager modules are provided in a distributedpeer-to-peer manner by multiple interacting server block data storagecomputing systems. In other embodiments, at least some of the serverblock data storage systems may be network storage devices that may lacksome I/O components and/or other components of physical computingsystems, such as if at least some of the provision and maintenance ofvolumes on those server storage systems is performed by other remotephysical computing systems (e.g., by a BDS System Manager moduleexecuting on one or more other computing systems). In addition, in someembodiments, at least some server block data storage systems eachmaintains multiple local hard disks, and stripes at least some volumesacross a portion of each of some or all of the local hard disks.Furthermore, various types of techniques for creating and using volumesmay be used, including in some embodiments to use LVM (“Logical VolumeManager”) technology.

In at least some embodiments, some or all block data storage volumeseach have copies stored on two or more distinct server block datastorage systems, such as to enhance reliability and availability of thevolumes. By doing so, failure of a single server block data storagesystem may not cause access of executing programs to a volume to belost, as use of that volume by those executing programs may be switchedto another available server block data storage system that has a copy ofthat volume. In such embodiments, consistency may be maintained betweenthe multiple copies of a volume on the multiple server block datastorage systems in various ways. For example, in some embodiments, oneof the server block data storage systems is designated as storing theprimary copy of the volume, and the other one or more server block datastorage systems are designated as storing mirror copies of the volume insuch embodiments, the server block data storage system that has theprimary volume copy (referred to as the “primary server block datastorage system” for the volume) may receive and handle data accessrequests for the volume, and in some such embodiments may further takeaction to maintain the consistency of the other minor volume copies(e.g., by sending update messages to the other server block data storagesystems that provide the mirror volume copies when data in the primaryvolume copy is modified, such as in a master-slave computingrelationship manner). Various types of volume consistency techniques maybe used, with additional details included below.

In addition to maintaining reliable and available access of executingprograms to block data storage volumes by moving or otherwisereplicating volume copies when server block data storage systems becomeunavailable, the block data storage service may perform other actions inother situations to maintain access of executing programs to block datastorage volumes. For example, if a first executing program unexpectedlybecomes unavailable, in some embodiments the block data storage serviceand/or program execution service may take actions to have a differentsecond executing program (e.g., a second copy of the same program thatis executing on a different host computing system) attach to some or allblock data storage volumes that were in use by the unavailable firstprogram, so that the second program can quickly take over at least someoperations of the unavailable first program. The second program may insome situations be a new program whose execution is initiated by theunavailability of the existing first program, while in other situationsthe second program may already be executing (e.g., if multiple programcopies are concurrently executed to share an overall load of work, suchas multiple Web server programs that receive different incoming clientrequests as mediated by a load balancer, with one of the multipleprogram copies being selected to be the second program; if the secondprogram is a standby copy of the program that is executing to allow a“hot” swap from the existing first program in the event ofunavailability, such as without the standby program copy being activelyused until the unavailability of the existing first program occurs;etc.). In addition, in some embodiments, a second program to which anexisting volume's attachment and ongoing use is switched may be onanother host physical computing system in the same geographical location(e.g., the same data center) as the first program, while in otherembodiments the second program may be at a different geographicallocation (e.g., a different data center, such as in conjunction with acopy of the volume that was previously or concurrently moved to thatother data center and will be used by that second program). Furthermore,in some embodiments, other related actions may be taken to furtherfacilitate the switch to the second program, such as by redirecting somecommunications intended for the unavailable first program to the secondprogram.

As previously noted, in at least some embodiments, some or all blockdata storage volumes each have copies stored on two or more distinctserver block data storage systems at a single geographical location,such as within the same data center in which executing programs willaccess the volume by locating all of the volume copies and executingprograms at the same data center or other geographical location, variousdesired data access characteristics may be maintained (e.g., based onone or more internal networks at that data center or other geographicallocation), such as latency and throughput. For example, in at least someembodiments, the described techniques may provide access to non-localblock data storage that has access characteristics that are similar toor better than access characteristics of local physical block datastorage devices, but with much greater reliability that is similar to orexceeds reliability characteristics of RAID (“Redundant Array ofIndependent (or Inexpensive) Disks”) systems and/or dedicated SANs(“Storage Area Networks”) and at much lower cost. In other embodiments,the primary and mirror copies for at least some volumes may instead bestored in other manners, such as at different geographical locations(e.g., different data centers), such as to further maintain availabilityof a volume even if an entire data center becomes unavailable. Inembodiments in which volume copies may be stored at differentgeographical locations, a user may in some situations request that aparticular program be executed proximate to a particular volume (e.g.,at the same data center at which the primary volume copy is located), orthat a particular volume be located proximate to a particular executingprogram, such as to provide relatively high network bandwidth and lowlatency for communications between the executing program and primaryvolume copy.

Furthermore, access to some or all of the described techniques may insome embodiments be provided in a fee-based or other paid manner to atleast some users. For example, users may pay one-time fees, periodic(e.g., monthly) fees and/or one or more types of usage-based fees to usethe block data storage service to store and access volumes, to use theprogram execution service to execute programs, and/or to use archivalstorage systems (e.g., provided by a remote long-term storage service)to store long-term backups or other snapshot copies of volumes. Fees maybe based on one or more factors and activities, such as indicated in thefollowing non-exclusive list: based on the size of a volume, such as tocreate the volume (e.g., as a one-time fee), to have ongoing storageand/or use of the volume (e.g., a monthly fee), etc.; based on non-sizecharacteristics of a volume, such as a number of mirror copies,characteristics of server block data storage systems (e.g., data accessrates, storage sizes, etc.) on which the primary and/or mirror volumecopies are stored, and/or a manner in which the volume is created (e.g.,a new volume that is empty, a new volume that is a copy of an existingvolume, a new volume that is a copy of a snapshot volume copy, etc.);based on the size of a snapshot volume copy, such as to create thesnapshot volume copy (e.g., as a one-time fee) and/or have ongoingstorage of the volume (e.g., a monthly fee); based on the non-sizecharacteristics of one or more snapshot volume copies, such as a numberof snapshots of a single volume, whether a snapshot copy is incrementalwith respect to one or more prior snapshot copies, etc.; based on usageof a volume, such as the amount of data transferred to and/or from avolume (e.g., to reflect an amount of network bandwidth used), a numberof data access requests sent to a volume, a number of executing programsthat attach to and use a volume (whether sequentially or concurrently),etc.; based on the amount of data transferred to and/or from a snapshot,such as in a manner similar to that for volumes; etc. In addition, theprovided access may have various forms in various embodiments, such as aonetime purchase fee, an ongoing rental fee, and/or based on anotherongoing subscription basis. Furthermore, in at least some embodimentsand situations, a first group of one or more users may provide data toother users on a fee-based basis, such as to charge the other users forreceiving access to current volumes and/or historical snapshot volumecopies created by one or more users of the first group (e.g., byallowing them to make new volumes that are copies of volumes and/or ofsnapshot volume copies; by allowing them to use one or more createdvolumes; etc.), whether as a one-time purchase fee, an ongoing rentalfee, or on another ongoing subscription basis.

In some embodiments, one or more application programming interfaces(APIs) may be provided by the block data storage service, programexecution service and/or remote long-term storage service, such as toallow other programs to programmatically initiate various types ofoperations to be performed (e.g., as directed by users of the otherprograms). Such operations may allow some or all of the previouslydescribed types of functionality to be invoked, and include, but are notlimited to, the following types of operations: to create, delete,attach, detach, or describe volumes; to create, delete, copy or describesnapshots; to specify access rights or other metadata for volumes and/orsnapshots; to manage execution of programs; to provide payment to obtainother types of functionality; to obtain reports and other informationabout use of capabilities of one or more of the services and/or aboutfees paid or owed for such use; etc. The operations provided by the APImay be invoked by, for example, executing programs on host computingsystems of the program execution service and/or by computing systems ofcustomers or other users that are external to the one or moregeographical locations used by the block data storage service and/orprogram execution service.

FIG. 1 illustrates an example network configuration 100 in whichmultiple computing systems are operable to execute various programs,applications, and/or services, and further operable to access reliablenon-local block data storage, such as under the control of a block datastorage service and/or program execution service, in accordance withvarious embodiments. In particular, in this example, a program executionservice manages the execution of programs on various host computingsystems located within a data center 102, and a block data storageservice uses multiple other server block data storage systems at thedata center to provide reliable non-local block data storage to thoseexecuting programs. Multiple remote archival storage systems external tothe data center may also be used to store additional copies of at leastsome portions of at least some block data storage volumes.

In this example, a data center 102 includes a number of racks 104, eachrack including a number of host computing devices 106, as well as anoptional rack support computing system 134 in this example embodiment.The host computing systems 106 on the illustrated rack 104 each host oneor more virtual machines 110 in this example, as well as a distinct NodeManager module 108 associated with the virtual machines on that hostcomputing system to manage those virtual machines. One or more otherhost computing systems 116 may also each host one or more virtualmachines 110 in this example. Each virtual machine 110 may act as anindependent computing node for executing one or more program copies (notshown) for a user (not shown), such as a customer of the programexecution service. In addition, this example data center 102 furtherincludes additional host computing systems 114 that do not includedistinct virtual machines, but may nonetheless each act as a computingnode for one or more programs (not shown) being executed for a user. Inthis example, a Node Manager module 112 executing on a computing system(not shown) distinct from the host computing systems 114 and 116 isassociated with those host computing systems to manage the computingnodes provided by those host computing systems, such as in a mannersimilar to the Node Manager modules 108 for the host computing systems106. The rack support computing system 134 may provide various utilityservices for other computing systems local to its rack 102 (e.g.,long-term program storage, metering, and other monitoring of programexecution and/or of non-local block data storage access performed byother computing systems local to the rack, etc.), as well as possibly toother computing systems located in the data center. Each computingsystem may also have one or more local attached storage devices (notshown), such as to store local copies of programs and/or data created byor otherwise used by the executing programs, as well as various othercomponents.

In this example, an optional computing system 118 is also illustratedthat executes a PES System Manager module for the program executionservice to assist in managing the execution of programs on the computingnodes provided by the host computing systems located within the datacenter (or optionally on computing systems located in one or more otherdata centers 128, or other remote computing systems 132 external to thedata center). As discussed in greater detail elsewhere, a PES SystemManager module may provide a variety of services in addition to managingexecution of programs, including the management of user accounts (e.g.,creation, deletion, billing, etc.); the registration, storage, anddistribution of programs to be executed; the collection and processingof performance and auditing data related to the execution of programs;the obtaining of payment from customers or other users for the executionof programs; etc. In some embodiments, the PES System Manager module maycoordinate with the Node Manager modules 108 and 112 to manage programexecution on computing nodes associated with the Node Manager modules,while in other embodiments the Node Manager modules may not assist inmanaging such execution of programs.

This example the data center 102 also includes a computing system 124that executes a Block Data Storage (“BDS”) system manager module for theblock data storage service to assist in managing the availability ofnon-local block data storage to programs executing on computing nodesprovided by the host computing systems located within the data center(or optionally on computing systems located in one or more other datacenters 128, or other remote computing systems 132 external to the datacenter). In particular, in this example, the data center 102 includes apool of multiple server block data storage systems 122, which each havelocal block storage for use in storing one or more volume copies 120.Access to the volume copies 120 is provided over the internal network(s)126 to programs executing on various computing nodes 110 and 114. Asdiscussed in greater detail elsewhere, a BDS System Manager module mayprovide a variety of services related to providing non-local block datastorage functionality, including the management of user accounts (e.g.,creation, deletion, billing, etc.); the creation, use and deletion ofblock data storage volumes and snapshot copies of those volumes; thecollection and processing of performance and auditing data related tothe use of block data storage volumes and snapshot copies of thosevolumes; the obtaining of payment from customers or other users for theuse of block data storage volumes and snapshot copies of those volumes;etc. In some embodiments, the BDS System Manager module may coordinatewith the Node Manager modules to manage use of volumes by programsexecuting on associated computing nodes, while in other embodiments theNode Manager modules may not be used to manage such volume use. Inaddition, in other embodiments, one or more BDS System Manager modulesmay be structured in other manners, such as to have multiple instancesof the BDS System Manager executing in a single data center (e.g., toshare the management of non-local block data storage by programsexecuting on the computing nodes provided by the host computing systemslocated within the data center), and/or such as to have at least some ofthe functionality of a BDS System Manager module being provided in adistributed manner by software executing on some or all of the serverblock data storage systems 122 (e.g., in a Peer to-peer manner, withoutany separate centralized BDS System Manager module on a computing system124).

In this example, the various host computing systems, server block datastorage systems, and computing systems are interconnected via one ormore internal networks 126 of the data center, which may include variousnetworking devices (e.g., routers, switches, gateways, etc.) that arenot shown. In addition, the internal networks 126 are connected to anexternal network 130 (e.g., the Internet or other public network) inthis example, and the data center 102 may further include one or moreoptional devices (not shown) at the interconnect between the data centerand an external network (e.g., network proxies, load balancers, networkaddress translation devices, etc.). In this example, the data center 102is connected via the external network 130 to one or more other datacenters 128 that each may include some or all of the computing systemsand storage systems illustrated with respect to data center 102, as wellas other remote computing systems 132 external to the data center. Theother computing systems 132 may be operated by various parties forvarious purposes, such as by the operator of the data center or thirdparties (e.g., customers of the program execution service and/or of theblock data storage service). In addition, one or more of the othercomputing systems may be archival storage systems (e.g., as part of aremote network-accessible storage service) with which the block datastorage service may interact, such as under control of one or morearchival manager modules (not shown) that execute on the one or moreother computing systems or instead on one or more computing systems ofthe data center, as described in greater detail elsewhere. Furthermore,while not illustrated here, in at least some embodiments, at least someof the server block data storage systems 122 may further beinterconnected with one or more other networks or other connectionmediums, such as a high-bandwidth connection over which the serverstorage systems 122 may share volume data (e.g., for purposes ofreplicating copies of volumes and/or maintaining consistency betweenprimary and mirror copies of volumes), with such a high-bandwidthconnection not being available to the various host computing systems inat least some such embodiments.

It will be appreciated that the example of FIG. 1 has been simplifiedfor the purposes of explanation, and that the number and organization ofhost computing systems, server block data storage systems and otherdevices may be much larger than what is depicted in FIG. 1. For example,as one illustrative embodiment, there may be approximately 4,000computing systems per data center, with at least some of those computingsystems being host computing systems that may each host fifteen virtualmachines, and/or with some of those computing systems being server blockdata storage systems that may each store several volume copies. If eachhosted virtual machine executes one program, then such a data center mayexecute as many as sixty thousand program copies at one time.Furthermore, hundreds or thousands (or more) volumes may be stored onthe server block data storage systems, depending on the number of serverstorage systems, size of the volumes, and number of mirror copies pervolume. It will be appreciated that in other embodiments, other numbersof computing systems, programs and volumes may be used.

FIG. 2 illustrates an example environment 200 including computingsystems suitable for managing the provision and use of reliablenon-local block data storage functionality to clients that can be usedin accordance with various embodiments. In this example, a managementsystem 202, such as one or more server computers including one or moreexternally-facing customer interfaces, is programmed to execute anembodiment of at least one BDS System Manager module 204 to manageprovisioning of non-local block data storage functionality to programsexecuting on host computing systems 208 and/or on at least some othercomputing systems 218, such as to block data storage volumes (not shown)provided by the server block data storage systems 220. Each of the hostcomputing systems 208 in this example also executes an embodiment of aNode Manager module 210 to manage access of programs 214 executing onthe host computing system to at least some of the non-local block datastorage volumes, such as in a coordinated manner with the BDS SystemManager module 204 over a network 216 (e.g., an internal network of adata center, not shown, that includes the computing systems 202, 208,220, and optionally at least some of the other computing systems 218).In other embodiments, some or all of the Node Manager modules 210 mayinstead manage one or more other computing systems (e.g., the othercomputing systems 218).

In addition, multiple server block data storage systems 220 areillustrated that each can store at least some of the non-local blockdata storage volumes (not shown) used by the executing programs 214,with access to those volumes also provided over the network 216 in thisexample. One or more of the server block data storage systems 220 mayalso each store a server software component (not shown) that managesoperation of one or more of the server block data storage systems, aswell as various information (not shown) about the data that is stored bythe server block data storage systems. Thus, in at least someembodiments, the server computing system 202 of FIG. 2 may correspond tothe computing system 124 of FIG. 1, one or more of the Node Managermodules 108 and 112 of FIG. 1 may correspond to the Node Manager modules210 of FIG. 2, and/or one or more of the server block data storagecomputing systems 220 of FIG. 2 may correspond to server block datastorage systems 122 of FIG. 1. In addition, in this example embodiment,multiple archival storage systems 222 are illustrated, which may storesnapshot copies and/or other copies of at least portions of at leastsome block data storage volumes stored on the server block data storagesystems 220. The archival storage systems 222 may also interact withsome or all of the computing systems 202, 208, and 220, and in someembodiments may be remote archival storage systems (e.g., of a remotestorage service, not shown) that interact with the computing systemsover one or more other external networks (not shown).

The other computing systems 218 may further include other proximate orremote computing systems of various types in at least some embodiments,including computing systems via which customers or other users of theblock data storage service interact with the management and/or hostsystems. Furthermore, one or more of the other computing systems 218 mayfurther execute a PES System Manager module to coordinate execution ofprograms on the host computing systems 208 and/or other host computingsystems 218, or the management system 202 or one of the otherillustrated computing systems may instead execute such a PES SystemManager module, although a PES System Manager module is not illustratedin this example.

In the illustrated embodiment, a Node Manager module 210 is executing inmemory in order to manage one or more other programs 214 executing inmemory on the computing system, such as on behalf of customers of theprogram execution service and/or block data storage service. In someembodiments, some or all of the computing systems 208 may host multiplevirtual machines, and if so, each of the executing programs 214 may bean entire virtual machine image (e.g., with an operating system and oneor more application programs) executing on a distinct hosted virtualmachine computing node. The Node Manager module 210 may similarly beexecuting on another hosted virtual machine, such as a privilegedvirtual machine monitor that manages the other hosted virtual machines.In other embodiments, the executing program copies 214 and the NodeManager module 210 may execute as distinct processes on a singleoperating system (not shown) executed on a single computing system 208.

The archival storage system 222 is operable to execute at least oneArchival Manager module 224 in order to manage operation of one or moreof the archival storage systems, such as on behalf of customers of theblock data storage service and/or of a distinct storage service thatprovides the archival storage systems. In other embodiments, theArchival Manager module(s) 224 may instead be executing on anothercomputing system, such as one of the other computing systems 218 or onthe management system 202 in conjunction with the BDS System Managermodule 204. In addition, while not illustrated here, in some embodimentsvarious information about the data that is stored by the archivalstorage systems 222 may be maintained in storage for the archivalstorage systems or elsewhere.

The BDS System Manager module 204 and Node Manager modules 210 may takevarious actions to manage the provisioning and/or use of reliablenon-local block data storage functionality to clients (e.g., executingprograms), as described in greater detail elsewhere. In this example,the BDS System Manager module 204 may maintain a database 206 thatincludes information about volumes stored on the server block datastorage systems 220 and/or on the archival storage systems 222 (e.g.,for use in managing the volumes), and may further store various otherinformation (not shown) about users or other aspects of the block datastorage service. In other embodiments, information about volumes may bestored in other manners, such as in a distributed manner by Node Managermodules 210 on their computing systems and/or by other computingsystems. In addition, in this example, each Node Manager module 210 on ahost computing system 208 may store information 212 about the currentvolumes attached to the host computing system and used by the executingprograms 214 on the host computing system, such as to coordinateinteractions with the server block data storage systems 220 that providethe primary copies of the volumes, and to determine how to switch to amirror copy of a volume if the primary volume copy becomes unavailable.While not illustrated here, each host computing system may furtherinclude a distinct logical local block data storage device interface foreach volume attached to the host computing system and used by a programexecuting on the computing system, which may further appear to theexecuting programs as being indistinguishable from one or more otherlocal physically attached storage devices that provide local storage.

An environment such as that illustrated with respect to FIGS. 1-2 can beused to provide and manage resources shared among various customers. Inone embodiment, a virtualized storage system can be provided using anumber of data servers, each having a number of storage devices (e.g.,storage disks) attached thereto. The storage system can expose thestorage to the customers as a Web service, for example. Customers thencan submit Web services requests, or other appropriate requests orcalls, to allocate storage on those servers and/or access that storagefrom the instances provisioned for those customers. In certainembodiments, a user is able to access the data volumes of these storagedevices as if those storage devices are conventional block devices.Since the data volumes will appear to the customer instances as if eachvolume is a disk drive or similar block device, the volumes can beaddressed with offsets, lengths, and other such conventional blockdevice aspects. Further, such a system can provide what will be referredto herein as “read after write” consistency, wherein data is guaranteedto be able to be read from the data as soon as the data is written toone of these data volumes. Such a system can provide relatively lowlatency, such as latencies less than about ten milliseconds. Such asystem thus in many ways functions as a traditional storage area network(SAN), but with improved performance and scalability.

Using a management system as illustrated in FIG. 2, for example, acustomer can make a Web service call into an appropriate API of a Webservice layer of the system to provision a data volume and attach thatvolume to a data instance for that customer. The management system canbe thought of as residing in a control plane, or control environment,with the data volumes and block storage devices residing in a separatedata plane, or data environment. In one example, a customer with atleast one provisioned instance can call a “CreateVolume” or similar API,via Web services, which enables the customer to specify the amountallows them to specify the amount of storage to be allocated, such as avalue between 1 GB and 1 TB, in 1 GB increments. Components of thecontrol plane, such as a BDS system manager module, can call into thedata plane to allocate the desired amount of storage from the availableresources, and can provide the customer with an identifier for the datavolume. In some embodiments, the customer then can call an“AttachVolume” or similar API, wherein the customer provides values forparameters such as an instance identifier, a volume identifier, and adevice name, depending on factors such as the operating system of theinstance, using a scheme that the operating system provides for harddrives and similar storage devices, as from inside the instance there isno apparent difference, from at least a functionality and naming pointof view, from a physical hard drive. Once the customer has attached thedata volume to a provisioned instance, the customer can perform variousfunctionality, such as to build a file system, use as raw storage for adata system, or any other such activity that would normally be performedwith a conventional storage device. When the customer no longer requiresthe data volume, or for any other appropriate reason, the customer cancall a “DetatchVolume” or similar API, which can cause the associationof the instance to that volume to be removed. In some embodiments, thecustomer can then attach a new instance or perform any of a number ofother such activities. Since the data volume will fail independently ofthe instances in some embodiments, the customer can attach a volume to anew instance if a currently associated instance fails.

In certain approaches, a customer requesting a data volume is not ableto select or request a particular type of volume, or a particular typeof performance. A customer is typically granted an amount of storage,and the performance follows a “best effort” type of approach, whereincustomer requests are performed based on the capability, load, and othersuch factors of the system at the time of the request. Each customer istypically charged the same amount per unit measure, such as the samedollar amount per gigabyte of storage per month, as well as the sameamount per number of I/O requests per month, charged in an amount suchas in increments of millions of requests per month.

As discussed above, however, such an approach can be problematic insituations such as where the number of requests waiting to be processedby an instance exceeds the ability of the instance to process thoserequests. Even if a customer is within the expected or allocated numberof requests for that customer, other customers submitting requests tothat instance can exceed their allocation, creating an overloadsituation where the data server for the instance can begin putting backpressure on the incoming requests in order to reduce the rate ofincoming requests and allow the system to move out of the overloadsituation. Thus, each customer on the device with pending requests canexperience a decrease in processing rate, as well as other issues suchas a decrease in available storage.

Systems and methods in accordance with various embodiments enablecustomers to ensure a minimum level of performance by enabling eachcustomer to specify one or more committed rates or other performanceguarantees. In addition to a minimum amount of storage, each customercan purchase a committed rate of operations, such as a specific numberof input/output (I/O) operations per second (IOPS). In previous systems,performance guarantees were obtained by dedicating an entire machine toa customer, along with dedicated bandwidth, etc., which often isoverkill. Embodiments discussed herein can allow customers to purchaseperformance guarantees at any appropriate level of granularity. Bymanaging the performance allocations for customers on various resources,systems and methods in accordance with various embodiments can enablecustomers to purchase volumes that have an IOPS guarantee at anyappropriate level, such as between 1 IOPS and 5,000 IOPS. By allocatingportions of disks, spindles, and other such resources, a system canoffer customers guaranteed levels of storage and/or IOPS.

Systems and methods in accordance with various embodiments allow usersto share resources, providing specific guarantees or commitments withrespect to those resources at a level of granularity that is notpossible with conventional solutions. In many cases, customers may wishto specify a minimum processing rate, such as a minimum number of I/Ooperations per second (IOPS). Approaches in accordance with variousembodiments can commit the desired amount of server and other resourcesnecessary to provide at least a committed level of performance. Bycommitting to a level of performance, a customer can receive aconsistent quality of service level that is not affected by theperformance of other customers sharing a device or resource. Even in anoverload situation, the customer can receive at least the guaranteedlevel of service. The amount of guaranteed service can depend uponvarious factors, as well as the amount specified and paid for by thecustomer.

For example, FIG. 3 illustrates an example distribution 300 wherein theprocessing capacity of a server 302 is allocated among severalcustomers. In this example, the server is determined to have a capacityfor about 500 IOPS. This value can be an estimated or average value, andcan be determined or adjusted over time based on monitored performanceor other such information. While all 500 IOPS can be allocated in someembodiments, it can be desirable in other embodiments to only allocate athreshold amount, percentage, or other portion of the total capacity asguarantees. Since the processing time for each request can vary, thenumber of IOPS at any given time can vary as well, such that allocatingall 500 IOPS might cause short periods of time where the customers areunable to receive their guarantees when the actual performance is on theorder of 450 IOPS due to the nature of the requests being processed,etc.

In this example, the system might be able to allocate up to 400 of the500 IOPS available for the server 302. As can be seen, Customer A hasbeen allocated a committed 200 IOPS, Customer B has been allocated acommitted 100 IOPS, and Customer C has been allocated a committed 55IOPS. The remaining customers on the server then can utilize a “bestperformance” or similar approach sharing the remaining 145 IOPS (onaverage). The number of customers sharing the remaining IOPS can beselected or limited based upon a number of factors, such that theremaining customers can still obtain a desirable level of performance alarge percentage of the time.

In many cases, however, Customers A, B, and C will not all utilize theirentire committed capacity. Each of those customers might pay toguarantee a level of performance such that the level is available whenneeded, but often will not actually be running near that peak capacity.In this situation, the remaining Customers D-Z can actually share morethan the remaining 145 IOPS, as those customers can utilize availablecapacity from the committed IOPS that are not being currently used. Thisprovides another advantage, as customers can receive guaranteed levelsof performance, but when those levels are not being fully utilized theremaining capacity can be used to service other customer requests. Suchan approach enables the regular customers (without guarantees) toreceive improved performance, without the need for the provider topurchase excess capacity or provide capacity that is not being utilizeda vast majority of the time.

In some embodiments, any of Customers A-C can exceed their performanceguarantees. For example, Customer A might, for a period of time, submitrequests on the order of 250 IOPS. For the 50 IOPS above the committedrate, those requests in some embodiments can be treated as normalrequests and processed at the same performance level as those ofcustomers D-Z. In an overload situation, any throttling, slow down, orother reduction in processing can then be applied to the 145 or so IOPSthat are not subject to guarantees. The guaranteed levels for CustomersA, B, and C will not be affected, as the overflow adjustments are madeto the non-committed portion. Accordingly, customers with non-guaranteedlevels of service can be charged lower prices per request, period, etc.

In other embodiments, when any of Customers A-C exceed its performanceguarantees, that customer can receive a “blended” or other level ofservice. In a situation where each request for a customer is treatedindividually or without context, such that any single request over acommitted rate can be treated as a request without a committed rate,there can be a negative impact on the other requests for that customer.For example, if Customer A has a committed rate of 250 IOPS and at onepoint issues 251 requests in a second, that single request over the ratecommitment can be processed much more slowly than the other requests,such as at 20 ms instead of 1 ms. If the customer application isexpecting a performance level of about 1 ms and experiences a slowdownwith respect to one request, that can have an impact on the processingof the other requests as well, and can cause a significant slowdown orother problems for the application even though the customer onlyslightly exceeded the threshold for a short period of time.

Systems and methods in accordance with various embodiments address sucha situation by providing a “boost” or blended rate to customers withrate guarantees who exceed those guarantees, which provides a level ofservice between a committed and uncommitted rate. For example, acustomer with a rate guarantee might have any excess requests placed ator near the front of the “queue” for uncommitted requests. In otherembodiments, the customer might receive a lower rate commitment forthose requests, such as might experience a delay of about 5 ms, whichare not processed at the same rate as requests within the committedrate, but are processed more quickly than for customers without acommitted rate. The amount of delay can be related in some embodimentsto the amount of overage and the length of time that the customer isover the guaranteed rate, to provide a relatively uniform degradation inperformance that is at least somewhat proportional to the amount ofoverage. For example, a customer with a guaranteed rate of 100 IOPS whois consistently sending requests at a rate of 500 per second wouldlikely not receive as much of a boost as a customer with a 250 IOPSguaranteed rate who occasionally goes over by a handful of requests. Insome embodiments, a customer can be provided with the same rate for anyoverage, but can be charged a premium for each such request. Many othervariations are possible as well within the scope of the variousembodiments.

To manage the commitments, components of a control plane can essentiallymake reservations against specific servers or other resources in thedata plane. In FIG. 3 where three customers want a total of 355 TOPScommitted, the control plane can reserve that level against a singleserver, for example, and allocate the remainder to any other customerprovisioned on that server. The control plane can also ensure that morevolumes are not allocated to a server than the server can handle, due tospace limitations, the number of I/Os that need to be generated, or anyother such factor.

In some cases, a customer might want a guaranteed level of service thatexceeds the “committable” capacity for a given resource. For example, inFIG. 3 it was stated that the server could allocate 400 IOPS, but 355are already allocated to Customers A-C. If another customer wants 300IOPS, that number would exceed the allowed amount (as well as theaverage capacity) of the server. Thus, the customer cannot receive thedesired commitment on that server. Using the management components ofthe control plane, however, the commitment rate can be allocated acrossmultiple servers. For example, in the allocation 400 of FIG. 4, it isshown that Customer A sends a request from a user device 402 requestinga guarantee of 300 IOPS. The control plane in some embodiments cansearch the available servers to determine if a server is available with300 IOPS left for guarantees. If not, the control plane can attempt tospread the IOPS across as few servers as possible. In this case, thecontrol plane determines to allocate the IOPS guarantee across threeservers, with a first server 404 providing a guarantee of 100 IOPS, asecond server 406 providing a guarantee of 125 IOPS, and a third server408 providing a guarantee of 75 IOPS. Thus, a volume does not need to beresident on a single server as in many conventional systems, but can bepartitioned across multiple servers. The allocation across multipleservers also enables customers to utilize larger data volumes, such asvolumes of 50 terabytes instead of 1 terabyte, as the data can be spreadacross multiple servers. In such an embodiment, a customer can purchasebetween 1 GB and 50 TB of storage, for example, with a desiredcommitment rate, such as a rate between 0 IOPS and 5,000 IOPS. Based onone or more of these values selected by a customer, the control planecan determine an appropriate, if not optimal, way to provide thoseguarantees using available resources in the data plane.

In some embodiments, the committed rate might be allocated up to 100% ofthe capacity of a server. An amount of un-committed usage can bepredicted and/or monitored, such that a number of customers can beallocated to resources that are fully committed, as long as the customeris willing to take resources only as they come available. Certaincustomers might not care when IOPS occur, particularly for certainwrites, such that they would be willing to pay a lower rate to utilizeresources that are guaranteed up to 100%, knowing that some customerslikely will not utilize their full guaranteed levels. Such an approachassists the provider in maximizing the utilization of each resource byallocating un-committed IOPS on resources that are otherwise “fully”committed.

Further, different types of customers will have different requirements.For example, if a disk has 100 TB of space and 100 IOPS capacity, afirst customer might want to store 90 TB of vacation photos that arerarely accessed. That customer might be interested in purchasing 90 TBof storage space along with an uncommitted level of IOPS. Another usermight want a 1 TB database that is going to be under constant use, suchthat the user might want about 100 IOPS. In this example, the firstcustomer could be sold 90% of the for storage, and the other customercan be allocated 90% (or more) of the IOPS of the disk as a commitment.Due to the nature of the customers, they both could be provisioned onthe same disk, where otherwise each might have required a dedicateddisk.

Enabling others to utilize the unused portion of a customer's committedallocation can benefit that customer as well, because the customer maynot have to pay for the entire allocation and thus can receive a lowercost that would be required for a dedicated resource. Further, thecustomer will still receive the guaranteed level of service. When thecustomer is at the full committed level, other customers on that devicewill have to reduce their rate of request or wait longer per request. Insome embodiments, a resource can be fully committed and other users canstill be provisioned on the device to utilize the unused portions of theresource. In some cases, where predictions and monitoring accuratelysupport such use, a resource can even be committed for over 100%, wherethe actual use by the allocated customers will almost never equal orsurpass 100% usage. In such an embodiment, there can be other resourcesthat can pick up any overage in the event of an unlikely event where theresource is overloaded.

In order to make commitments on a new resource (or new instance of aresource), certain default information can be used to make commitments.It can be desirable to use relatively conservative numbers as thedefaults, in order to prevent over-committing a resource. For example, acontrol plane component can use general default information that eachspindle of a particular type can handle 100-120 IOPS. If there aretwelve spindles per server, there can be about 1200-1440 IOPS availableper server. The control plane components can be conservative, initially,and can allocate a first amount, such as up to 400 TOPS, until moreinformation is gained about the performance and usage of that resource.In certain examples customer utilization is about 10%, such that in manyinstances customers are using only 10% of the available IOPS. Thus,dedicating 40% to guaranteed TOPS would still be four times more than isactually being used, and thus likely is still a conservative number.Each server in the data plane can track the amount of available space onthe server, and can store the number of IOPS that are committed for thatserver. Thus, when a new volume is to be created, the control planecomponents can determine a server that, out of that 400 TOPS, has enoughcapacity available that the server is willing to commit for that volume.An approach in one embodiment is to ask servers, at random or in aparticular order, whether they can take a specific number of TOPS, andthis continues until a server is located that can accept the IOPS. Whenthe information is also stored in the control plane, however, thecontrol plane can select an appropriate server first and then contactthat server to take the volume.

Using components such as those discussed above, FIG. 5 illustrates anexample process 500 by which a customer can request a guaranteed levelof service, or committed rate of processing, in accordance with variousembodiments. As should be understood, the illustrated steps areexamples, and that additional, fewer, or alternative steps can beperformed in similar or alternative orders, or in parallel, within thescope of the various embodiments. Further, the process can be performedfor any appropriate components or elements, such as at least one datainstance, repository, or other such data source in a data environment,here a data plane, using a control plane or a similar data controlapplication or service. While the term “customer” is used herein torefer to the “owner” of specific data, or a data store or instancehosted by the system, it should be understood that the term customer isused merely for convenience, and that any appropriate user or developercan be allowed to access resources in the various embodiments.

A request, such as a Web services call, is received through one of aplurality of control plane APIs or other such customer-facing interfacecomponents 502. The request can be analyzed to determine any actionsneeded to process the request 504. As discussed elsewhere herein, thiscan take the form of a component of a Web services layer parsing therequest to determine the action(s) being requested. In an embodimentwhere the API receiving the request corresponds to a specific action tobe performed, the Web services layer can extract information from therequest to be used in determining aspects or parameters of the action tobe performed. In some instances where more than one action is required,the system can assemble an appropriate workflow. Different tasks can beselected for the workflow based upon factors such as the type ofaction(s) requested and the parameters of the request.

In one embodiment, the management or control system attempts todetermine and/or locate an available resource operable to provide therequested service with the requested guarantee level 506. In someembodiments this includes searching against a table of the managementsystem, or other repository in the control plane, to determine whether aresource has the desired capacity. In other embodiments, this caninvolve host systems or node managers at random, or in a particularorder, to determine whether each server has the desired capacity. Whenan available resource is located, a determination is made as to whetherthe requested commitment rate exceeds the available and/or thresholdamount of that resource 508. As should be understood, in someembodiments the steps of locating an available resource and determiningwhether that resource has sufficient capacity could be performed in asingle step.

If the resource has sufficient capacity such that the requestedcommitment rate would not exceed the allowable threshold of theresource, the commitment can be provided on that resource for thecustomer 510. If no single resource is located with sufficient capacityin this example, a determination is made as to whether there are otherresources with available capacity such that the commitment can beprovided using multiple resources 512. In some embodiments, the abilityto allocate across multiple devices can be limited in part by the sizeof the request, as it can be undesirable to spread across too manydevices, such as by using twenty servers to provide twenty IOPS for asingle customer. If there is an acceptable combination of resources toprovide the requested commitment, the committed rate can be split overmultiple resource instances 514. If there is not an adequate combinationof resources to provide the requested rate, the commitment can be denied516. Once a decision is made as to the commitment, a message is sent tothe requesting customer (or another appropriate user, application, orlocation) that the requested action has been completed 518. At anappropriate time after a commitment is approved, the customer can beallocated to one or more resources and the resource can be notified ofthe appropriate level of service to be provided for requests associatedwith that customer. After the commitment is applied and any necessaryconfiguration or provisioning actions performed, the customer is able todirectly access the resource for which the guarantee was applied 520. Ifthe action is performed with respect to a resource other than a datainstance in a data environment, then native or direct access to theresource can be provided through the target environment using anotherappropriate interface. As mentioned, the user can provided with a DNSaddress and port number, for example, such that if the action resultedin movement of data or another similar action, the customer or anapplication can continue to use the same DNS address, which will bedirected to the appropriate location in the data plane.

By providing commitments at varying granularities, a provider canprovide a number of different pricing schemes. For example, a user mightpay a certain amount for each committed IOPS, such as $0.30 perguaranteed IOPS, whether or not the user actually uses that amount.Thus, if a user purchases a commitment of 100 IOPS for a month, the userwould pay $30 regardless of the actual usage, as the user is paying forthe commitment. Various other pricing approaches can be used as well,such as various tiered pricing schemes. In other embodiments, a usermight pay a premium for a level of committed IOPS, but that amount mightbe offset by the amount of unused commitment that was utilized by otherusers. For example, a user might pay $30 for 100 IOPS for a month, butif on average other users utilized 25 of those committed IOPS allocatedto that customer, the customer might see a reduction such as $0.05 perIOPS, for a total monthly fee of $25.

As discussed, a customer might go over their committed amount as well.Various pricing approaches can be used for these extra IOPS within thescope of various embodiments. In one embodiment, the customer is chargedthe same for the excess IOPS as any customer having un-committed IOPS(e.g., $0.10 per IOPS), and the customer requests are treated the sameas these requests. In other embodiments, the customer can select to payextra per IOPS to be handled with the other requests, but given priorityover standard requests. In some embodiments, a customer can pay apremium to have their excess requests processed within the availablecommitted resources of another customer, such that the requests will behandled as a committed request as long as at least one other customer onthe resource is below their level of commitment. While customers maywant the ability to spike request rates if needed, in certainembodiments users might be capped at a certain level, whether to limitcustomer costs, ensure certain levels of quality of service, or forother such reasons. The ability to exceed guaranteed levels can also bebeneficial to customers who are scaling a system or application, as thecustomer can determine areas of need without suffering significantly inquality of service.

FIG. 6 illustrates an example of an environment 600 that can utilizeand/or take advantage of aspects in accordance with various embodiments.As will be appreciated, although a Web-based environment is used forpurposes of explanation, different environments may be used, asappropriate, to implement various embodiments. The environment 600 shownincludes both a testing or development portion (or side) and aproduction portion. The production portion includes an electronic clientdevice 602, which can include any appropriate device operable to sendand receive requests, messages, or information over an appropriatenetwork 604 and convey information back to a user of the device.Examples of such client devices include personal computers, cell phones,handheld messaging devices, laptop computers, set-top boxes, personaldata assistants, electronic book readers, and the like. The network caninclude any appropriate network, including an intranet, the Internet, acellular network, a local area network, or any other such network orcombination thereof. Components used for such a system can depend atleast in part upon the type of network and/or environment selected.Protocols and components for communicating via such a network are wellknown and will not be discussed herein in detail. Communication over thenetwork can be enabled by wired or wireless connections, andcombinations thereof. In this example, the network includes theInternet, as the environment includes a Web server 606 for receivingrequests and serving content in response thereto, although for othernetworks an alternative device serving a similar purpose could be usedas would be apparent to one of ordinary skill in the art.

The illustrative environment includes at least one application server608 and a data store 610. It should be understood that there can beseveral application servers, layers, or other elements, processes, orcomponents, which may be chained or otherwise configured, which caninteract to perform tasks such as obtaining data from an appropriatedata store. As used herein the term “data store” refers to any device orcombination of devices capable of storing, accessing, and retrievingdata, which may include any combination and number of data servers,databases, data storage devices, and data storage media, in anystandard, distributed, or clustered environment. The application servercan include any appropriate hardware and software for integrating withthe data store as needed to execute aspects of one or more applicationsfor the client device, handling a majority of the data access andbusiness logic for an application. The application server providesaccess control services in cooperation with the data store, and is ableto generate content such as text, graphics, audio, and/or video to betransferred to the user, which may be served to the user by the Webserver in the form of HTML, XML, or another appropriate structuredlanguage in this example. The handling of all requests and responses, aswell as the delivery of content between the client device 602 and theapplication server 608, can be handled by the Web server. It should beunderstood that the Web and application servers are not required and aremerely example components, as structured code discussed herein can beexecuted on any appropriate device or host machine as discussedelsewhere herein. Further, the environment can be architected in such away that a test automation framework can be provided as a service towhich a user or application can subscribe. A test automation frameworkcan be provided as an implementation of any of the various testingpatterns discussed herein, although various other implementations can beused as well, as discussed or suggested herein.

The environment also includes a development and/or testing side, whichincludes a user device 618 allowing a user such as a developer, dataadministrator, or tester to access the system. The user device 618 canbe any appropriate device or machine, such as is described above withrespect to the client device 602. The environment also includes adevelopment server 620, which functions similar to the applicationserver 608 but typically runs code during development and testing beforethe code is deployed and executed on the production side and isaccessible to outside users, for example. In some embodiments, anapplication server can function as a development server, and separateproduction and testing storage may not be used.

The data store 610 can include several separate data tables, databases,or other data storage mechanisms and media for storing data relating toa particular aspect. For example, the data store illustrated includesmechanisms for storing production data 612 and user information 616,which can be used to serve content for the production side. The datastore also is shown to include a mechanism for storing testing data 614,which can be used with the user information for the testing side. Itshould be understood that there can be many other aspects that may needto be stored in the data store, such as for page image information andaccess right information, which can be stored in any of the above listedmechanisms as appropriate or in additional mechanisms in the data store610. The data store 610 is operable, through logic associated therewith,to receive instructions from the application server 608 or developmentserver 620, and obtain, update, or otherwise process data in responsethereto. In one example, a user might submit a search request for acertain type of item. In this case, the data store might access the userinformation to verify the identity of the user, and can access thecatalog detail information to obtain information about items of thattype. The information then can be returned to the user, such as in aresults listing on a Web page that the user is able to view via abrowser on the user device 602. Information for a particular item ofinterest can be viewed in a dedicated page or window of the browser.

Each server typically will include an operating system that providesexecutable program instructions for the general administration andoperation of that server, and typically will include a computer-readablemedium storing instructions that, when executed by a processor of theserver, allow the server to perform its intended functions. Suitableimplementations for the operating system and general functionality ofthe servers are known or commercially available, and are readilyimplemented by persons having ordinary skill in the art, particularly inlight of the disclosure herein.

The environment in one embodiment is a distributed computing environmentutilizing several computer systems and components that areinterconnected via communication links, using one or more computernetworks or direct connections. However, it will be appreciated by thoseof ordinary skill in the art that such a system could operate equallywell in a system having fewer or a greater number of components than areillustrated in FIG. 6. Thus, the depiction of the system 600 in FIG. 6should be taken as being illustrative in nature, and not limiting to thescope of the disclosure.

An environment such as that illustrated in FIG. 6 can be useful for aprovider such as an electronic marketplace, wherein multiple hosts mightbe used to perform tasks such as serving content, authenticating users,performing payment transactions, or performing any of a number of othersuch tasks. Some of these hosts may be configured to offer the samefunctionality, while other servers might be configured to perform atleast some different functions. The electronic environment in such casesmight include additional components and/or other arrangements, such asthose illustrated in the configuration 200 of FIG. 2, discussed indetail below.

As discussed above, the various embodiments can be implemented in a widevariety of operating environments, which in some cases can include oneor more user computers, computing devices, or processing devices whichcan be used to operate any of a number of applications. User or clientdevices can include any of a number of general purpose personalcomputers, such as desktop or laptop computers running a standardoperating system, as well as cellular, wireless, and handheld devicesrunning mobile software and capable of supporting a number of networkingand messaging protocols. Such a system also can include a number ofworkstations running any of a variety of commercially-availableoperating systems and other known applications for purposes such asdevelopment and database management. These devices also can includeother electronic devices, such as dummy terminals, thin-clients, gamingsystems, and other devices capable of communicating via a network.

Various aspects also can be implemented as part of at least one serviceor Web service, such as may be part of a service-oriented architecture.Services such as Web services can communicate using any appropriate typeof messaging, such as by using messages in extensible markup language(XML) format and exchanged using an appropriate protocol such as SOAP(derived from the “Simple Object Access Protocol”). Processes providedor executed by such services can be written in any appropriate language,such as the Web Services Description Language (WSDL). Using a languagesuch as WSDL allows for functionality such as the automated generationof client-side code in various SOAP frameworks.

Most embodiments utilize at least one network that would be familiar tothose skilled in the art for supporting communications using any of avariety of commercially-available protocols, such as TCP/IP, OSI, FTP,UPnP, NFS, CIFS, and AppleTalk. The network can be, for example, a localarea network, a wide-area network, a virtual private network, theInternet, an intranet, an extranet, a public switched telephone network,an infrared network, a wireless network, and any combination thereof.

In embodiments utilizing a Web server, the Web server can run any of avariety of server or mid-tier applications, including HTTP servers, FTPservers, CGI servers, data servers, Java servers, and businessapplication servers. The server(s) also may be capable of executingprograms or scripts in response requests from user devices, such as byexecuting one or more Web applications that may be implemented as one ormore scripts or programs written in any programming language, such asJava®, C, C# or C++, or any scripting language, such as Perl, Python, orTCL, as well as combinations thereof. The server(s) may also includedatabase servers, including without limitation those commerciallyavailable from Oracle®, Microsoft®, Sybase®, and IBM®.

The environment can include a variety of data stores and other memoryand storage media as discussed above. These can reside in a variety oflocations, such as on a storage medium local to (and/or resident in) oneor more of the computers or remote from any or all of the computersacross the network. In a particular set of embodiments, the informationmay reside in a storage-area network (“SAN”) familiar to those skilledin the art. Similarly, any necessary files for performing the functionsattributed to the computers, servers, or other network devices may bestored locally and/or remotely, as appropriate. Where a system includescomputerized devices, each such device can include hardware elementsthat may be electrically coupled via a bus, the elements including, forexample, at least one central processing unit (CPU), at least one inputdevice (e.g., a mouse, keyboard, controller, touch screen, or keypad),and at least one output device (e.g., a display device, printer, orspeaker). Such a system may also include one or more storage devices,such as disk drives, optical storage devices, and solid-state storagedevices such as random access memory (“RAM”) or read-only memory(“ROM”), as well as removable media devices, memory cards, flash cards,etc.

Such devices also can include a computer-readable storage media reader,a communications device (e.g., a modem, a network card (wireless orwired), an infrared communication device, etc.), and working memory asdescribed above. The computer-readable storage media reader can beconnected with, or configured to receive, a computer-readable storagemedium, representing remote, local, fixed, and/or removable storagedevices as well as storage media for temporarily and/or more permanentlycontaining, storing, transmitting, and retrieving computer-readableinformation. The system and various devices also typically will includea number of software applications, modules, services, or other elementslocated within at least one working memory device, including anoperating system and application programs, such as a client applicationor Web browser. It should be appreciated that alternate embodiments mayhave numerous variations from that described above. For example,customized hardware might also be used and/or particular elements mightbe implemented in hardware, software (including portable software, suchas applets), or both. Further, connection to other computing devicessuch as network input/output devices may be employed.

Storage media and computer readable media for containing code, orportions of code, can include any appropriate media known or used in theart, including storage media and communication media, such as but notlimited to volatile and non-volatile, removable and non-removable mediaimplemented in any method or technology for storage and/or transmissionof information such as computer readable instructions, data structures,program modules, or other data, including RAM, ROM, EEPROM, flash memoryor other memory technology, CD-ROM, digital versatile disk (DVD) orother optical storage, magnetic cassettes, magnetic tape, magnetic diskstorage or other magnetic storage devices, or any other medium which canbe used to store the desired information and which can be accessed bythe a system device. Based on the disclosure and teachings providedherein, a person of ordinary skill in the art will appreciate other waysand/or methods to implement the various embodiments.

The specification and drawings are, accordingly, to be regarded in anillustrative rather than a restrictive sense. It will, however, beevident that various modifications and changes may be made thereuntowithout departing from the broader spirit and scope of the invention asset forth in the claims.

1. A computer-implemented method of committing processing rates forcustomers of shared resources, comprising: under control of one or morecomputer systems configured with executable instructions, receiving arequest for a committed rate of input/output operations per second(IOPS) for a shared resource in a data environment, the request capableof specifying a committed rate corresponding to any portion of a ratecapacity of one or more instances of the shared resource, the requestbeing received as a Web service request to at least one applicationprogramming interface (API); determining at least one instance availablein the data environment; and if the determined at least one instance iscapable of providing the committed rate corresponding to the request:sending at least one request to the determined at least one instance inthe data environment to commit at least a portion of the committed rateto the user; storing information for the determined at least oneinstance and the committed rate to a management data store; and sendinga message to the user indicating whether the committed rate is approved.2. The computer-implemented method of claim 1, wherein determining atleast one instance available in the data environment includes analyzingcommitment information for a plurality of instances in the dataenvironment, the commitment information being stored in the managementdata store.
 3. The computer-implemented method of claim 1, wherein ifthe determined at least one instance is not capable of providing thecommitted rate corresponding to the request, the request for a committedrate is denied.
 4. A computer-implemented method of managing usage ofshared computing resources, comprising: under control of one or morecomputer systems configured with executable instructions, receiving arequest for a committed usage rate for a type of resource, the requestcapable of specifying a committed usage rate corresponding to anyportion of a usage capacity of one or more instances of the type ofresource; determining at least one instance of the type of resourceoperable to provide at least a portion of the requested committed usagerate; and assigning at least a portion of the requested committed usagerate to each determined instance when the at least one determinedinstance is capable of providing the committed usage rate, wherein thecommitted usage rate is capable of being supplied by a single determinedinstance or a plurality of determined instances each providing at leasta portion of the requested committed usage rate, each determinedinstance further capable of having additional users sharing the resourcewhen usage capacity for the instance allows for the additional users,and wherein a user is able to request a committed usage rate that issubstantially independent of the capacity of any single instance of thetype of resource.
 5. The computer-implemented method of claim 4, whereinthe committed usage rate for a type of resource is a committed rate ofinput/output operations per second (TOPS) for a data server.
 6. Thecomputer-implemented method of claim 4, wherein determining at least oneinstance of the type of resource operable to provide at least a portionof the requested committed usage rate includes determining at least oneinstance having at least an allowable portion of the capacity of thatinstance uncommitted to other users.
 7. The computer-implemented methodof claim 4, wherein if no combination of instances is determined to becapable of providing the committed usage rate corresponding to therequest, the request is denied.
 8. The computer-implemented method ofclaim 4, wherein each instance is capable of supporting committedrequest rates for multiple users, each instance further capable ofsupporting requests for additional users.
 9. The computer-implementedmethod of claim 8, wherein at least one instance is configured toprocess requests for users with uncommitted request rates using anuncommitted or unused portion of the capacity of the instance, andwherein in an overload situation the requests for users with committedusage rates are processed at a normal rate and requests for userswithout committed usage rates are slowed down to overcome the overloadsituation.
 10. The computer-implemented method of claim 4, wherein auser with a committed usage rate is able to exceed the committed usagerate, any request over the committed usage rate being processed at arate for requests without rate commitments or at a blended rate betweenrates for requests with and without rate commitments.
 11. Thecomputer-implemented method of claim 4, wherein determining at least oneinstance of the type of resource operable to provide at least a portionof the requested committed usage rate includes randomly contactinginstances for at least one of capacity or commitment information. 12.The computer-implemented method of claim 4, further comprising: chargingeach user based at least in part on the committed usage rate for thattype of resource for that user.
 13. A computer-implemented method forhandling input/output (I/O) requests for a shared resource, comprising:enabling at least one user of a shared resource to receive a committedrate of I/O operations per second (IOPS) with respect to the sharedresource, the committed rate being less than or equal to an IOPS ratecapacity of the shared resource; upon receiving a first request from theat least one user having received a committed rate of IOPS, processingthe first request against the shared resource; and upon receiving asecond request from an additional user not having received a committedrate of IOPS, processing the second request if an uncommitted portion ofthe I/O rate capacity is available or if a committed portion of the IOPSrate capacity is not being used.
 14. The computer-implemented method ofclaim 13, wherein a rate of processing requests from users withoutcommitted usage rates is slowed when the shared resource is in anoverload situation.
 15. The computer-implemented method of claim 13,further comprising: upon receiving a third request from a specific userof the at least one user having received a committed rate of IOPS, wherethe third request causes the specific user to exceed the committed usagerate for the specific user, processing the third request at a rate forrequests without rate commitments or at a blended rate between rates forrequests with and without rate commitments.
 16. A system for managingusage of a shared computing resource, comprising: at least oneprocessor; and memory including instructions that, when executed by theat least one processor, cause the system to: receive a request for acommitted usage rate for a type of resource, the request capable ofspecifying a committed usage rate corresponding to any portion of ausage capacity of one or more instances of the type of resource;determine at least one instance of the type of resource operable toprovide at least a portion of the requested committed usage rate; andassign at least a portion of the requested committed usage rate to eachdetermined instance when the at least one determined instance is capableof providing the committed usage rate, wherein the committed usage rateis capable of being supplied by a single determined instance or aplurality of determined instances each providing at least a portion ofthe requested committed usage rate, each determined instance furthercapable of having additional users sharing the resource when usagecapacity for the instance allows for the additional users, and wherein auser is able to request a committed usage rate that is substantiallyindependent of the capacity of any single instance of the type ofresource.
 17. The system of claim 16, wherein the committed usage ratefor a type of resource is a committed rate of input/output operationsper second (IOPS) for a data server.
 18. The system of claim 16, whereindetermining at least one instance of the type of resource operable toprovide at least a portion of the requested committed usage rateincludes determining at least one instance having at least an allowableportion of the capacity of that instance uncommitted to other users. 19.The system of claim 16, wherein each instance is capable of supportingcommitted request rates for multiple users, each instance furthercapable of supporting requests for additional users.
 20. The system ofclaim 16, wherein at least one instance is configured to processrequests for users with uncommitted request rates using an uncommittedor unused portion of the capacity of the instance, and wherein in anoverload situation the requests for users with committed usage rates areprocessed at a normal rate and requests for users without committedusage rates are slowed down to overcome the overload situation.
 21. Acomputer-readable storage medium managing usage of a shared computingresource, the instructions when executed by a processor causing theprocessor to: receive a request for a committed usage rate for a type ofresource, the request capable of specifying a committed usage ratecorresponding to any portion of a usage capacity of one or moreinstances of the type of resource; determine at least one instance ofthe type of resource operable to provide at least a portion of therequested committed usage rate; and assign at least a portion of therequested committed usage rate to each determined instance when the atleast one determined instance is capable of providing the committedusage rate, wherein the committed usage rate is capable of beingsupplied by a single determined instance or a plurality of determinedinstances each providing at least a portion of the requested committedusage rate, each determined instance further capable of havingadditional users sharing the resource when usage capacity for theinstance allows for the additional users, and wherein a user is able torequest a committed usage rate that is substantially independent of thecapacity of any single instance of the type of resource.
 22. Thecomputer-readable storage medium of claim 16, wherein the committedusage rate for a type of resource is a committed rate of input/outputoperations per second (IOPS) for a data server.
 23. Thecomputer-readable storage medium of claim 21, wherein determining atleast one instance of the type of resource operable to provide at leasta portion of the requested committed usage rate includes determining atleast one instance having at least an allowable portion of the capacityof that instance uncommitted to other users.
 24. The computer-readablestorage medium of claim 21, wherein each instance is capable ofsupporting committed request rates for multiple users, each instancefurther capable of supporting requests for additional users.
 25. Thecomputer-readable storage medium of claim 21, wherein at least oneinstance is configured to process requests for users with uncommittedrequest rates using an uncommitted or unused portion of the capacity ofthe instance, and wherein in an overload situation the requests forusers with committed usage rates are processed at a normal rate andrequests for users without committed usage rates are slowed down toovercome the overload situation.